Delete compile_results.py

compile_results.py

@@ -1,154 +0,0 @@
-#!/usr/bin/env python3
-"""Merge row-level metrics with judge annotations into compiled benchmark files."""
-
-from __future__ import annotations
-
-import argparse
-from pathlib import Path
-from typing import Dict, Iterable, Iterator, Tuple
-
-from apm_metrics import flatten_judge_fields, load_json_or_jsonl, write_json
-
-
-TEXT_FIELDS = (
-    "clean_text",
-    "noisy_prompt",
-    "model_response",
-    "response",
-    "assisted_prompt",
-    "mediated_prompt",
-)
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument(
-        "--metrics-root",
-        type=Path,
-        required=True,
-        help="Root containing <model>/<noise>/metrics.json files.",
-    )
-    parser.add_argument(
-        "--judged-root",
-        type=Path,
-        required=True,
-        help="Root containing <model>/<noise>/results.jsonl files with judge annotations.",
-    )
-    parser.add_argument(
-        "--output-root",
-        type=Path,
-        default=Path("compiled"),
-        help="Directory where compiled JSON files will be written.",
-    )
-    parser.add_argument(
-        "--include-text-fields",
-        action="store_true",
-        help="Include source prompts and model responses when present.",
-    )
-    return parser.parse_args()
-
-
-def judged_file(noise_dir: Path) -> Path | None:
-    for preferred in ("results.jsonl", "results.json"):
-        path = noise_dir / preferred
-        if path.exists():
-            return path
-
-    candidates = sorted(
-        path for path in noise_dir.iterdir() if path.is_file() and path.suffix in {".json", ".jsonl"}
-    )
-    return candidates[0] if candidates else None
-
-
-def discover_judged(judged_root: Path) -> Iterator[Tuple[str, str, Path]]:
-    for model_dir in sorted(path for path in judged_root.iterdir() if path.is_dir()):
-        for noise_dir in sorted(path for path in model_dir.iterdir() if path.is_dir()):
-            path = judged_file(noise_dir)
-            if path is not None:
-                yield model_dir.name, noise_dir.name, path
-
-
-def compile_file(
-    *,
-    model: str,
-    noise: str,
-    metrics_path: Path,
-    judged_path: Path,
-    output_path: Path,
-    include_text_fields: bool,
-) -> Tuple[int, int]:
-    metrics = load_json_or_jsonl(metrics_path)
-    judged = load_json_or_jsonl(judged_path)
-
-    metrics_by_id: Dict[str, Dict] = {
-        row["example_id"]: row for row in metrics if row.get("example_id") is not None
-    }
-
-    compiled = []
-    missing = 0
-
-    for judged_row in judged:
-        ex_id = judged_row.get("example_id")
-        metric_row = metrics_by_id.get(ex_id)
-        if metric_row is None:
-            missing += 1
-            continue
-
-        row = {
-            "example_id": ex_id,
-            "model": metric_row.get("model") or judged_row.get("model") or model,
-            "noise": metric_row.get("noise") or judged_row.get("noise") or noise,
-        }
-
-        for key, value in metric_row.items():
-            if key not in {"example_id", "model", "noise"}:
-                row[key] = value
-
-        row.update(flatten_judge_fields(judged_row))
-
-        if include_text_fields:
-            for key in TEXT_FIELDS:
-                if key in judged_row:
-                    row[key] = judged_row[key]
-
-        compiled.append(row)
-
-    write_json(compiled, output_path)
-    return len(compiled), missing
-
-
-def main() -> None:
-    args = parse_args()
-
-    total_rows = 0
-    total_missing = 0
-    total_files = 0
-
-    for model, noise, judged_path in discover_judged(args.judged_root):
-        metrics_path = args.metrics_root / model / noise / "metrics.json"
-        if not metrics_path.exists():
-            print(f"Skipping {model}/{noise}: missing {metrics_path}")
-            continue
-
-        output_path = args.output_root / model / noise / "compiled.json"
-        rows, missing = compile_file(
-            model=model,
-            noise=noise,
-            metrics_path=metrics_path,
-            judged_path=judged_path,
-            output_path=output_path,
-            include_text_fields=args.include_text_fields,
-        )
-        total_rows += rows
-        total_missing += missing
-        total_files += 1
-        print(f"{model}/{noise}: {rows} compiled rows, {missing} missing metrics -> {output_path}")
-
-    print(
-        f"Compiled {total_rows} rows from {total_files} files; "
-        f"{total_missing} judged rows had no matching metric row"
-    )
-
-
-if __name__ == "__main__":
-    main()